# HazyResearch/data-centric-ai

Resources for Data Centric AI

Repository: https://github.com/HazyResearch/data-centric-ai
Canonical: https://ross.abutalabs.com/products/hazyresearch-data-centric-ai
Language: TeX
License: Apache-2.0
License Family: permissive
Topics: machine-learning, ai, artificial-intelligence, data-centric-ai
Last push: 2023-12-13T09:58:57+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1909, "days_push": 994, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1147, forks 120 (observed 2026-08-28T04:03:46.012271+00:00)

## What it is
A curated, opinionated collection of resources, papers, and progress on Data-Centric AI from the Hazy Research group at Stanford. It organizes topics like weak supervision, data augmentation, data cleaning, robustness, and MLOps into a structured reading guide.

## Use cases
- learn about data-centric ai
- find papers on weak supervision and data programming
- study data augmentation and cleaning techniques for machine learning
- prepare a course or reading list on data quality for ML
- explore mlops and data selection resources
- understand why data matters more than models in production ai

## When to choose
- you want a curated starting point for data-centric AI research and concepts
- you are building a curriculum or self-study plan around data quality in ML
- you want links to papers, case studies, and related awesome lists in one place

## When to avoid
- you need runnable code, libraries, or tools rather than reading material
- you need up-to-date coverage, as several sections are stubs or under construction
- you want an unbiased survey rather than an opinionated viewpoint

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, machine-learning
- domain: machine-learning, data-science, artificial-intelligence, tutorials
- platform: cross-platform
- tags: data-centric-ai, curated-list, awesome-list, research-resources, mlops, data-quality

## Member repositories
- HazyResearch/data-centric-ai (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:46.012271+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:33:53.403433+00:00, confidence not recorded.
  - readme: https://github.com/HazyResearch/data-centric-ai (fetched 2026-08-28T04:03:46.012271+00:00, sha 6eac8f310cac)
- Data as of 2026-08-30T08:39:29.467469+00:00.